Architect, Data Engineer (SAP + Databricks)

Founded in 2017, Lovelytics has helped some of the most complex enterprises across industries such as Energy & Utilities, Media & Entertainment, Manufacturing and Retail & CPG, modernize their data and put AI to work, not in a deck, but in production. We move fast, stay close to the cutting edge, and care more about outcomes than optics.

Our work spans the full data and AI lifecycle: Data Strategy & Advisory, Data Engineering, Analytics & Visualization, Generative AI & ML, and Cloud Migration & Modernization — all delivered on Databricks, with deep partnerships across AWS, Azure, and GCP. To date, we've delivered over $2B in business value for Fortune 500 clients.

In the last year, Lovelytics has grown from 85 to 500+ people across the Americas, all while keeping the technically excellent, low-ego culture that makes the work worth doing, earning us a Best Places to Work recognition and a spot among Databricks' top partners.

Lovelytics is seeking an experienced Data Architect with SAP expertise to lead the design and delivery of complex data engineering and integration solutions for our clients. This client-facing role will focus on architecting scalable, high-performing data solutions that integrate SAP data with modern cloud technologies, including Databricks, AWS, and Azure.

The ideal candidate brings deep SAP data expertise, strong technical leadership, and the ability to translate complex business requirements into effective architectural solutions. We're looking for someone who thrives in a collaborative, dynamic environment and shares our passion for bringing meaning to data.

This role is open to remote candidates in the US.

This role is not open for work sponsorship at this time.

Primary Responsibilities

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Lead the end-to-end architecture, design, and delivery of complex data engineering and SAP integration solutions.

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Serve as the technical lead on client engagements, owning architectural decisions and ensuring solutions align with business objectives and technical requirements.

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Design scalable, secure, and high-performing data architectures leveraging Databricks, AWS, Azure, and other relevant technologies.

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Architect SAP data integration solutions involving ECC and/or S/4HANA, leveraging deep knowledge of SAP tables, data structures, and underlying business processes.

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Define data integration strategies and best practices utilizing SAP technologies such as Datasphere, BW, HANA, or Business Data Cloud (BDC).

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Provide technical oversight of ETL/ELT pipelines, data warehousing, data modeling, and real-time data processing solutions.

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Establish architectural standards and best practices for data quality, security, governance, CI/CD, and performance optimization.

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Lead technical discovery sessions, architecture workshops, and solution design discussions with client stakeholders.

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Partner with Engagement Managers and Delivery Leads to define technical scope, project estimates, and implementation strategies.

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Provide technical guidance and mentorship to engineering teams, ensuring high-quality delivery and adherence to architectural standards.

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Identify technical risks, evaluate architectural tradeoffs, and proactively recommend solutions to complex challenges.

Our Ideal Candidate's Skills and Experience

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Bachelor's degree in Computer Science, Engineering, or equivalent professional experience.

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8+ years of experience in data engineering, data architecture, or related technical disciplines, including experience leading complex technical solutions.

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Extensive hands-on experience with Databricks , including designing and implementing scalable data engineering solutions. Required.

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Deep understanding of SAP ERP data architecture (ECC and/or S/4HANA), including underlying tables, data relationships, and business processes.

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Strong experience with at least one SAP data integration technology: SAP Datasphere, SAP BW, SAP HANA, or SAP Business Data Cloud (BDC).

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Proven experience designing SAP-to-cloud data integration solutions and enterprise data architectures.

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Advanced knowledge of data warehousing, lakehouse architecture, data modeling, ETL/ELT, and cloud technologies (AWS and/or Azure).

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Strong understanding of data security, governance, CI/CD, and performance optimization.

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Demonstrated ability to independently lead technical engagements, guide engineering teams, and make architectural decisions.

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Excellent client-facing communication skills, with the ability to translate business requirements into technical solutions and present recommendations to stakeholders.

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Experience working in a consulting or professional services environment preferred.

What We Promise You

• Exciting projects with great clients in varying departments and verticals across the world

• The ability to work closely with experienced data engineers and quickly grow and expand your skillset

• The ability to work closely with all sizes of companies, ranging from Fortune 100 to small local businesses

• A workplace where you are encouraged to challenge the status quo and develop new technologies, methodologies, and processes

• A diverse team consisting of data gurus, experience seekers, and entrepreneurial minds that are always pushing to be better

The base salary range for this position for candidates based in the US is  $150,000-$215,000.00  per year. Compensation is determined based on a variety of factors including, but not limited to, relevant experience, skills, qualifications, scope of role and budget. Candidates are not guaranteed to be placed at any particular point within the range, and most offers will fall within the middle of the range or below. Lovelytics is committed to pay equity and transparency in compensation practices.

Lovelytics is an Equal Opportunity Employer. This means you don’t have to worry about whether your application process will be fair. We consider all applicants without regard to race, color, religion, age, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, veteran status, or disability.